The Cancer Risk From Low Level Radiation: A Review of Recent Evidence

This article deals with an aspect of the biological science underlying health risk analysis. Many vitamins and minerals have been known to promote health in small doses and cause disease in high doses for some time. Accumulating evidence indicates that ionizing radiation and other agents also interact with biological systems in similar fashion. The phenomenon is called "hormesis." Hormesis is now being considered as a general biological phenomenon (e.g., cf. Linda M. Gerber, George C. Williams and Sandra J. Gray, "The Nutrient-Toxin Dosage Continuum in Human Evolution and Modern Health," Sept. 1999, The Quarterly Review of Biology, Vol. 74, No. 3, pp. 273-289.)

Prof. Cohen reviews some of the accumulating evidence about biological responses to ionizing radiation. The theoretical and practical implications of this evidence are life-threatening and life-saving. For example, if ionizing radiation exposure is over-regulated, individual and societal resources are wasted in attempts to reduce harmless or even healthful radiation exposure dosages. These wasted resources would be better applied to improving the conditions of human life. Wasted resources kill.

Radiation protection regulators often claim that they try to err on the side of caution. But in doing so, regulators in the past have ignored the evidence of hormesis in response to ionizing radiation. To look at only the bad effects of radiation and be blind to the good effects is comparable to banning penicillin based on the fact that penicillin can kill by anaphylaxis while ignoring lives saved by the substance.

In addition to harming peoples' health, public health policies based on incomplete evaluation of scientific evidence harm the reputation of science in the mind of the public. Science and the public reputation of science advance only when all pertinent evidence is considered.

Robert J. Cihak, MD Editorial Board member

Background

In the past, the cancer risk from low level radiation (LLR) has been estimated by use of a linear-no threshold hypothesis (LNT). This hypothesis assumes that a single particle of radiation interacting with a single DNA molecule can initiate a cancer; if the assumption were correct, the number of initiating events would be proportional to the number of particles of radiation, and hence to the radiation dose. LNT is frequently extrapolated to doses as low as 1/10,000 of those for which there is direct evidence of cancer induction by radiation. This extrapolation is the origin of the commonly used expression "no level of radiation is safe" and the consequent public fear of LLR. This article explores some of the scientific evidence bearing on this hypothesis.

Recent discoveries show that DNA damage events occur all the time in our bodies, due to natural metabolic processes. Each human cell averages more than 200,000 damage events every day. Reparative biochemical mechanisms continually repair this damage. Double-strand breaks (DSB) in DNA are more significant and occur much less frequently.

The hypothesis most favorable for LNT is that double-strand breaks (DSB) are the cancer initiators. An average cell experiences about 200 spontaneous DSB per year, whereas 10 cSv (10 rem) of radiation gives the average cell only 4 DSB.(1) Thus a hypothetical lifetime exposure of 10 cSv (10 rem)/year increases cancer initiating events by only 2% (4/200); however, LNT predicts that it should increase cancer risk by more than 150%. (10 rem/yr is about 50 times greater than the average annual human background radiation exposure.)

Biological Defense Mechanisms (BDM)

One problem with the rationale for LNT is that it does not consider the role of biological defense mechanisms (BDM) which prevent each of the trillions of potentially cancer initiating events each human experiences every year from developing into a fatal cancer. Another problem is the abundant evidence that LLR stimulates BDM(2); this fact implies that LLR should prevent development of cancer. We cite here a few examples. Current evidence indicates that cancers are initiated by genetic damage in a cell nucleus. Chromosome aberrations are one type of widely studied genetic damage. In both in vitro and in vivo experiments on various type cells,(3,4) exposure to LLR substantially reduces the number of chromosome aberrations from subsequent exposure to large radiation doses; this effect is ascribed to stimulated production of repair enzymes by the LLR.

Mutations are another type of genetic damage; prior LLR also reduces induction of specific detectable gene mutations in cells later exposed to high level radiation — both in vitro(5) and in vivo.6

Perhaps more directly relevant, exposures to LLR can reduce the rate of subsequent spontaneous neoplastic transformation in cells by 3-fold or more.(7)

LLR stimulates the immune system, an important contributor to BDM.(8,9) Direct observation of repair of DNA base damage has shown that a gamma radiation dose of 25 cSv (25 rem) 4 hours before a 200 cSv (200 rem) dose, reduced the time for 50% lesion removal from 100 minutes to 50 minutes.(10) In other words, DNA lesions healed more quickly if an initial, stimulating radiation dose was given.

Since exposure to low level radiation stimulates BDM, this healing effect must be added to the harmful effect of cancer initiations hypothesized by LNT, effectively reducing the total risk predictions based on LNT alone. If the healing effects of stimulated BDM are larger than the carcinogenic effects hypothesized by LNT in the low dose region, the net effect of LLR is to protect against cancer; this is called "hormesis."

Risk vs Dose Data From Human Ionizing Radiation Exposures

Decisions on dose-response public health guidelines should be most heavily weighted on experiences with realistic human radiation exposure doses and timing. The principal data cited by supporters of LNT are solid tumors (all cancers except leukemia), among the Japanese A-bomb survivors, and an International Association for Research on Cancer (IARC) study of occupational doses to radiation workers. The A-bomb radiation exposure was at a high dose rate over a short time period in contrast with the low dose rate over a long time of concern in public health. The A-bomb data are shown in Figure 1, where the error bars represent 95% confidence limits (2 standard deviations).(11) At first glance, the points appear to suggest a linear relationship with intercept near zero dose but when the statistical error bars are considered, there is no statistically significant indication of excess cancers for doses below 25 cSv (25 rem), a dose about 100 times higher than the average human background radiation dose of about 0.2 rem. The data in Figure 1 can easily be explained by assuming a linear-no threshold dose-response relationship (labeled LNT) plus a stimulation of biological defense mechanisms at low dose (small dot line); adding these gives the resultant large-dot line at low dose merging into the LNT line.

The IARC (International Agency for Research on Cancer) study covered 95,673 monitored radiation workers in U.S., U.K., and Canada.(12) For all cancers except leukemia, there were 3,830 deaths but no excess over the number expected. The risk is reported as -.0007/cSv; there is surely no support for LNT here. These radiation doses were spread out over time in contrast with the instantaneous exposure experienced by the A-bomb survivors. Such long-term exposure is more relevant in establishing population and public health radiation exposure guidelines.

However, for the 146 leukemia deaths, they do report a positive risk vs dose relationship and claim that this supports LNT. Their data, listed in Table 1, obviously give no indication of an excess risk below 40 cSv (40 rem). The authors' conclusion that their data support LNT is based on an analysis which arbitrarily discards data points for which the observed to expected ratio (o/e) is less than unity! They thus discard 3 of the 7 data points.

On the other hand, there is much evidence that contradicts LNT. For example, the data on leukemia among A-bomb survivors are shown in Figure 2, with error bars indicating 95% confidence limits.(11) These data strongly suggest a threshold above 20 cSv (20 rem). Similar behavior is found for breast cancer among Canadian women exposed over longer periods of time to X-ray fluoroscopic examinations for tuberculosis(13); when appropriately evaluated, this evidence shows a decrease in risk with increasing radiation dose at least up to 20 cSv (20 rem).

The data on lung cancer among these Canadian women,(14) and similar U.S. data(15) are shown in Figure 3. Here again we see a decrease in the low dose region, extending at least up to 100 cSv. In Figure 3 these data are compared with lung cancer data for the Japanese A-bomb survivors, showing a clear difference between the two data sets, best explained by the difference between the nearly instantaneous and very high dose rate in the A-bomb survivors and the low dose rate from protracted fluoroscopic exams carried out over many months. This indicates that A-bomb survivor data (Figure 1) is quite limited in its value in predicting possible risks from chronic LLR, as the radiation of concern is received by the American public over a lifetime.

Figure 3. Relative Risk of mortality from lung cancer vs dose to lung, with 95% confidence limits. In lower figure with expanded vertical scale, circles are from Howe (14) and diamond is from Davis(15). In upper figure, solid line connects data from Canadian fluoroscopy patients, and dashed line connects data from A-bomb survivors.(14)

Powerful evidence against LNT is also found in studies of bone cancers among those exposed to ingested radium, as shown in Figure 4.(16) Evans' elaborate analysis essentially demonstrates threshold behavior. Such a threshold behavior is also strongly supported with much better statistics in studies of radioactivity injected into animals.(17)

Figure 4. Data on dial painters, chemists, and other exposed to ingested radium. Ordinate is percent in each dose category that had tumors in the bone or head, and abscissa is the dose in cGy (rad) to the skeleton. For doses above 1000 cGy, error bars are one standard elevation. There were no tumors for doses below 1000 cGy; asterisks show the ordinate if there had been one tumor in the dose category. A higher dose data point at 20,000 cGy with ordinate 38% (+/-13%) is off the plot.(16)

Dependence of Latent Period on Dose

A substantial body of data, both on animals and on humans, indicates that the latent period between carcinogenic radiation exposure and cancer death increases with decreasing exposure.(17,18) For low exposures, the theoretical latent period exceeds the normal life span, so no actual cancers develop. This latency effect alone, even in the absence of all considerations discussed previously, would invalidate LNT for LLR.

Lung Cancer Rate vs Radon Exposure in U.S. Counties

One test of LNT has no statistical uncertainty.(19,20) Plots of age-adjusted lung cancer mortality rates in U.S. counties, m, vs average radon level in homes, r, are shown for males and females respectively, in Figures 5a, 5c; rather than showing individual points for each county we have grouped them into intervals of r (shown on the base-line along with the number of counties in each group) and we plot the mean value of m for each group, its standard deviation, and the first and third quartiles of the distributions. Figures 5b, 5d show these data corrected for smoking prevalence. We see from Figure 5 that lung cancer rates decrease with increasing r, in sharp contrast to the increase expected from LNT, shown by the line labeled "theory," demonstrating the inverse of LNT predictions in this low dose region.

Actually, Figure 5 was only the beginning of a long and thorough study of possible explanations for this discrepancy; the possible effects of over 500 methodological problems and confounding factors were exhaustively analyzed without finding an even remotely plausible explanation consistent with LNT. For example, the large negative slopes in Figure 5 are found if we consider only the very urban counties or only the very rural; if we consider only the richest counties or only the poorest; if we consider only the counties with the best medical care or only those with the poorest medical care; if we consider only the wettest areas, or only the driest; if we consider only the warmest areas, or only the coolest areas; and so forth for all of the 500 potential confounding factors. The large negative slopes are also found for all strata in between, as, for example, considering only counties of average urbanicity, or only counties of average wealth, or only counties of average medical care, or only counties of average temperature, or only counties of average rainfall, etc. By far, the most plausible explanation for this discrepancy with theory is that LNT fails, grossly over-estimating the cancer risk in the low dose, low dose rate region.